Tony Peng
About Tony Peng
Tony Peng is a Development Engineer at Geospace Technologies, where he has worked since 2018. He holds a Bachelor's degree in Physics from National Tsing Hua University, a Master's degree in Physics, and a Ph.D. in Materials Engineering from the University of Maryland.
Work at Geospace Technologies
Tony Peng has been employed as a Development Engineer at Geospace Technologies since 2018. His role involves the design and implementation of systems related to sensor technologies. He is based in the Austin, Texas area and has contributed to various projects that enhance the company's capabilities in sensor data analysis and performance modeling.
Education and Expertise
Tony Peng holds a Bachelor's degree in Physics from National Tsing Hua University. He also earned a Master's degree in Physics from National Cheng Kung University. Furthering his education, he obtained a Ph.D. in Materials Engineering from the University of Maryland, focusing on Fiber Optic Sensors. His academic background provides a strong foundation for his work in sensor technologies and data analysis.
Background
Prior to his current position, Tony Peng worked at PGS as a Senior Engineer for 11 years, from 2007 to 2018, in the Austin, Texas area. He also served as a Research Engineer at Prime Photonics LC for three years, from 2003 to 2006, in Blacksburg, VA. His diverse experience in engineering roles has equipped him with a comprehensive understanding of sensor systems and data analysis.
Achievements
Tony Peng has designed and created a MySQL database with normalized tables and views for component test data analysis. He developed algorithms to model the reliability and performance of complex sensor systems, which led to reduced evaluation time. Additionally, he automated the analysis of sensor system characteristics using Python, significantly improving efficiency in data processing.
Technical Contributions
Tony Peng has made significant technical contributions, including the creation of a spatial network graph of complex fiber-optic sensor systems using the GIS tool QGIS. He constructed a new analysis platform using Python, which resulted in a tenfold savings of analysis time compared to traditional methods. His work also involved applying Six Sigma Failure Modes and Effects Analysis (FMEA) to identify high-risk features in sensor networks.